General multi-attack detection for continuous-variable quantum key distribution with local local oscillator

doi:10.1088/1674-1056/ad2bf2

中国物理B ›› 2024, Vol. 33 ›› Issue (5): 50308-050308.doi: 10.1088/1674-1056/ad2bf2

General multi-attack detection for continuous-variable quantum key distribution with local local oscillator

Zhuo Kang(康茁), Wei-Qi Liu(刘维琪)†, Jin Qi(齐锦), and Chen He(贺晨)

School of Information Science and Technology, Northwest University, Xi'an 710127, China

收稿日期:2023-12-13 修回日期:2024-02-01 接受日期:2024-02-22 出版日期:2024-05-20 发布日期:2024-05-20
通讯作者: Wei-Qi Liu E-mail:vickylwq1991@nwu.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 62001383).

General multi-attack detection for continuous-variable quantum key distribution with local local oscillator

Zhuo Kang(康茁), Wei-Qi Liu(刘维琪)†, Jin Qi(齐锦), and Chen He(贺晨)

School of Information Science and Technology, Northwest University, Xi'an 710127, China

Received:2023-12-13 Revised:2024-02-01 Accepted:2024-02-22 Online:2024-05-20 Published:2024-05-20
Contact: Wei-Qi Liu E-mail:vickylwq1991@nwu.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 62001383).

摘要/Abstract

摘要： Continuous-variable quantum key distribution with a local local oscillator (LLO CVQKD) has been extensively researched due to its simplicity and security. For practical security of an LLO CVQKD system, there are two main attack modes referred to as reference pulse attack and polarization attack presently. However, there is currently no general defense strategy against such attacks, and the security of the system needs further investigation. Here, we employ a deep learning framework called generative adversarial networks (GANs) to detect both attacks. We first analyze the data in different cases, derive a feature vector as input to a GAN model, and then show the training and testing process of the GAN model for attack classification. The proposed model has two parts, a discriminator and a generator, both of which employ a convolutional neural network (CNN) to improve accuracy. Simulation results show that the proposed scheme can detect and classify attacks without reducing the secret key rate and the maximum transmission distance. It only establishes a detection model by monitoring features of the pulse without adding additional devices.

关键词: CVQKD, generative adversarial network, attack classification

Abstract: Continuous-variable quantum key distribution with a local local oscillator (LLO CVQKD) has been extensively researched due to its simplicity and security. For practical security of an LLO CVQKD system, there are two main attack modes referred to as reference pulse attack and polarization attack presently. However, there is currently no general defense strategy against such attacks, and the security of the system needs further investigation. Here, we employ a deep learning framework called generative adversarial networks (GANs) to detect both attacks. We first analyze the data in different cases, derive a feature vector as input to a GAN model, and then show the training and testing process of the GAN model for attack classification. The proposed model has two parts, a discriminator and a generator, both of which employ a convolutional neural network (CNN) to improve accuracy. Simulation results show that the proposed scheme can detect and classify attacks without reducing the secret key rate and the maximum transmission distance. It only establishes a detection model by monitoring features of the pulse without adding additional devices.

Key words: CVQKD, generative adversarial network, attack classification

中图分类号: (Quantum communication)

03.67.Hk

03.67.Dd (Quantum cryptography and communication security) 03.67.-a (Quantum information)

Zhuo Kang(康茁), Wei-Qi Liu(刘维琪), Jin Qi(齐锦), and Chen He(贺晨). General multi-attack detection for continuous-variable quantum key distribution with local local oscillator[J]. 中国物理B, 2024, 33(5): 50308-050308.

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General multi-attack detection for continuous-variable quantum key distribution with local local oscillator

General multi-attack detection for continuous-variable quantum key distribution with local local oscillator

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